1. Field of the Invention
The present invention relates to a system for recommending desired programs or channels to internet protocol television (IPTV) users, and more particularly to a system for recommending personalized favorite programs or channels to IPTV users based on a collaborative filtering algorithm.
2. Description of the Related Art
As an internet protocol (IP)-based infrastructure is added to existing television (TV) receiving infrastructures, such as terrestrial broadcasting, cable broadcasting, and satellite broadcasting, the number of programs that users can select is infinite. For this reason, it is important and difficult for users to accurately and rapidly search for and select desired programs. Technology enabling such search and selection will be very useful. This may be assumed when considering usefulness and value at search engines, such as Google, on the Internet. Consequently, it will be very useful if a search tool, such as Google, can be used even in a TV viewing domain in which the number of programs that can be viewed is infinitely increased as in the Internet. However, it should be recognized that basic behavior patterns of users are different when using the Internet and viewing TV. That is, when using the Internet, a user inputs a desired keyword using a keyboard in a lean-forward posture in which the user sits at a personal computer (PC) on a desk in an office. When viewing TV, on the other hand, a user searches and selects a desired channel while simply changing channels from left to right and up and down using a remote controller in a lean-back posture in which the user lays on a sofa in a living room. When viewing TV, therefore, input is not carried out using an explicit method, such as keyboard input, but using an implicit method. Consequently, search is carried out through navigation of a hierarchical menu in a manner similar to search and selection of a program on a fixed menu as in early Yahoo. As the number of channels and programs is gradually increased, however, such a method has become a fundamental obstacle to a long tail market such as is found on the Internet. That is, most of the produced TV programs are not selected by viewers or are laid unused. For example, 30 million hours of programs are produced in America a year. Since the average TV viewing time per year per person is 16,400 hours, however, 0.005% of the produced programs are viewed and 99.995% of the produced programs are laid unused. Also, in case of an IPTV, navigation or program change time is too slow during search of programs to directly see and select the programs with the result that search is not substantially possible.
Meanwhile, broadcast information or an electronic program guide (EPG) provided through broadcast reception or a network in the existing TV or set top box (STB)/personal video recorder (PVR) provides broadcast programs in various manners.
However, it is very inconvenient and difficult for a user to select and view a desired program on a time-based broadcast information screen using an electronic program guide (EPG) configured in an enormous table form when more than 10,000 channels are present.
The most representative method of the electronic program guide is two-dimensional provision of a channel-based/time-based table or a one-dimensional provision of currently broadcast channel information.
Alternatively, such EPG information may be edited to display favorite channels in an EPG form. This displays channels in predetermined order, and the order may be changed according to a favorite degree of individuals.
So far, however, a technology of estimating a favorite degree of a user group based on a favorite degree of another user group and providing a recommended program list has not been proposed.
An IPTV is a service to provide users with TV contents through the Internet. The IPTV provides bi-directional services to the users unlike existing terrestrial broadcasting, cable broadcasting, and satellite broadcasting service systems. Fields related to the present invention include interactive TV related technologies. Specifically, fields related to the present invention include a high-ranking contents service platform technology, a broadband communication network technology, a load distribution technology, and a set top box (SIB) hardware, software, and remote control technology. A favorite program recommendation technology is referred to as a collaborative filtering technology, which quantifies a relation degree between viewers or users and programs, stores the quantified relation degree between viewers or users and programs in a database, and calculates a favorite degree from the quantified relation degree between viewers or users and programs stored in the database.
Collaborative filtering is a technology used in a personalization and recommendation algorithm. Specifically, collaborative filtering is a technology of estimating a favorite degree of a user based on a favorite degree of another user group to programs. Such a collaborative filtering technology has already widely used on electronic commerce sites, such as amazon.com, to recommend goods. Also, the collaborative filtering technology has been widely used in portal sites to recommend associative search words or associative motion pictures.
Such a collaborative filtering (CF) method includes a memory-based CF method, a model-based method, and a hybrid or contents-based CF method. In the memory-based CF method, it is necessary to first calculate similarity between users or items. A weighted value of a favorite degree is calculated based on the similarity, and a recommended program list is generated according to the weighted value. To this end, a correlation-based similarity calculation method and a vector cosine-based similarity calculation method are representatively used. An estimated value of a favorite degree of an active user to a new item is calculated using these methods, and a recommended program list is generated based on the estimated value.